Research Interests
My early work concentrated on development of "metrics that matter" — standardized methods for assessment of clinical outcomes important to clinicians, patients, families, and other stakeholders. Most notable of this would be the development of the ICHOM Standard Set for the Comprehensive Appraisal of Cleft Care and collaborations with groups such as Americleft, the ERN, and the CLEFT-Q™ team.
Development of metrics would be ineffectual unless these metrics were disseminated, adopted, and implemented by multidisciplinary teams. To that end, the second phase of my work focused on building the Allied Cleft & Craniofacial Quality-Improvement and Research Network (ACCQUIREnet).
Presently, my research is focused on using real-world data (RWD) and causal inference frameworks to improve observational (cohort) studies and embedded pragmatic clinical trials within ACCQUIREnet.
Interests: clinical outcomes research; patient-reported outcome measures (PROMs); comparative effectiveness research; health-technology assessment (HTA); dissemination and implementation (D&I) science; causal inference; pragmatic clinical trials (PCT); observational studies; real-world data (RWD); real-world evidence (RWE); data science; informatics; data visualization; geospatial analysis; network analysis; machine learning; artificial intelligence; biostatistics; Bayesian statistics.
Development of metrics would be ineffectual unless these metrics were disseminated, adopted, and implemented by multidisciplinary teams. To that end, the second phase of my work focused on building the Allied Cleft & Craniofacial Quality-Improvement and Research Network (ACCQUIREnet).
Presently, my research is focused on using real-world data (RWD) and causal inference frameworks to improve observational (cohort) studies and embedded pragmatic clinical trials within ACCQUIREnet.
Interests: clinical outcomes research; patient-reported outcome measures (PROMs); comparative effectiveness research; health-technology assessment (HTA); dissemination and implementation (D&I) science; causal inference; pragmatic clinical trials (PCT); observational studies; real-world data (RWD); real-world evidence (RWE); data science; informatics; data visualization; geospatial analysis; network analysis; machine learning; artificial intelligence; biostatistics; Bayesian statistics.